Proceedings of the 3rd workshop on Data management for sensor networks in conjunction with VLDB 2006 - DMSN '06

Abstract

The past few years have seen substantial amounts of computer science research on sensor networks as they have the potential to bring an unprecedented level of access to the physical world. Other subfields of Computer Science have had a number of workshops on the topic. Also, there are now at least two major conferences --- the Conference on Information Processing in Sensor Networks (IPSN), started in 2002 (the 2006 IPSN was held in April), and the ACM Conference on Sensor Systems (SenSys), started in 2003 (the 2006 SenSys will be held in November). These conferences have published a small number of database papers, but there is no exclusive forum for discussion on early and innovative work on data management in sensor networks. We believe that the DMSN 2006 workshop, building on the successes of the DMSN 2004 and DMSN 2005 workshops, fills a significant gap in the database and sensor network communities, by bringing together interested researchers and practitioners from different fields to identify interesting challenges and opportunities. Specifically, the workshop focuses on the challenges of data processing and management in networks of remote, wireless, battery-powered sensing devices (sensor networks). The power-constrained, lossy, noisy, distributed, and remote nature of such networks means that traditional data management techniques often cannot be applied without significant re-tooling. Furthermore, new challenges associated with acquisition and processing of live sensor data mean that completely new database techniques must also be developed. The DMSN workshop encompasses a wide range of topics which include: data replication and consistency in sensor network environments, database languages for sensor tasking, distributed data storage and indexing, energy-efficient data acquisition and dissemination, in-network query processing, integration of sensor network data into traditional and streaming data management systems, networking support for data processing, techniques for managing loss, uncertainty, and noise, query optimization, and privacy protection for sensory data.